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The scale and complexity of campus networks continues to accelerate due to recent paradigms such as the Internet of Things (IoT) resulting in a heightened awareness of the need for enhanced cybersecurity. Traditional cybersecurity approaches such as the placement of firewalls and other policy enforcement mechanisms at strategic choke points effectively divide the network into zones and are unable to regulate intrazone host-to-host communication. This traditional approach introduces significant risk as there is little in place to prevent the horizontal propagation of malware or other unwanted traffic within a given zone. In this paper we explore approaches for improving cybersecurity in campus networks by analyzing contemporary campus traffic patterns and propose several architectural enhancements in light of these patterns which introduce strategically placed hardware or hardware-accelerated software data planes which are evaluated from performance and effectiveness perspectives. 

Software defined networking (SDN) allows organizations to modify networks programmatically to implement custom forwarding behavior and to react to changing conditions. While there are many approaches available to implement SDN those that leverage forwarding table abstractions such as OpenFlow and P4 require developers to decompose problems into one or more tables associated with a definable pipeline. This paper explores tradeoffs between table depth and pipeline length associated with different problem decomposition options by analyzing the performance impact on hardware and software data planes including software data planes leveraging hardware acceleration through the use of SmartNICs.